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Social and Behavioral Sciences Commons™
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Articles 1 - 2 of 2
Full-Text Articles in Social and Behavioral Sciences
Evaluating The Impact Of Sandbox Applications On Live Digital Forensics Investigation, Reem Bashir, Helge Janicke, Wen Zeng
Evaluating The Impact Of Sandbox Applications On Live Digital Forensics Investigation, Reem Bashir, Helge Janicke, Wen Zeng
Research outputs 2014 to 2021
Sandbox applications can be used as anti-forensics techniques to hide important evidence in the digital forensics investigation. There is limited research on sandboxing technologies, and the existing researches on sandboxing are focusing on the technology itself. The impact of sandbox applications on live digital forensics investigation has not been systematically analysed and documented. In this study, we proposed a methodology to analyse sandbox applications on Windows systems. The impact of having standalone sandbox applications on Windows operating systems image was evaluated. Experiments were conducted to examine the artefacts of three sandbox applications: Sandboxie, BufferZone and ToolWiz Time Freeze on Windows …
Quantifying The Need For Supervised Machine Learning In Conducting Live Forensic Analysis Of Emergent Configurations (Eco) In Iot Environments, Victor R. Kebande, Richard A. Ikuesan, Nickson M. Karie, Sadi Alawadi, Kim-Kwang Raymond Choo, Arafat Al-Dhaqm
Quantifying The Need For Supervised Machine Learning In Conducting Live Forensic Analysis Of Emergent Configurations (Eco) In Iot Environments, Victor R. Kebande, Richard A. Ikuesan, Nickson M. Karie, Sadi Alawadi, Kim-Kwang Raymond Choo, Arafat Al-Dhaqm
Research outputs 2014 to 2021
© 2020 The Author(s) Machine learning has been shown as a promising approach to mine larger datasets, such as those that comprise data from a broad range of Internet of Things devices, across complex environment(s) to solve different problems. This paper surveys existing literature on the potential of using supervised classical machine learning techniques, such as K-Nearest Neigbour, Support Vector Machines, Naive Bayes and Random Forest algorithms, in performing live digital forensics for different IoT configurations. There are also a number of challenges associated with the use of machine learning techniques, as discussed in this paper.